Level Set Methods for Geometric Inverse Problems in Linear Elasticity

In this paper we investigate the regularization and numerical solution of geometric inverse problems related to linear elasticity with minimal assumptions on the geometry of the solution. In particular we consider the probably severely ill-posed reconstruction problem of a twodimensional inclusion from a single boundary measurement. In order to avoid parameterizations, which would introduce a-priori assumptions on the geometric structure of the solution, we employ the level set method for the numerical solution of the reconstruction problem. With this approach we construct an evolution of shapes with a normal velocity chosen in dependence of the shape derivative of the corresponding leastsquares functional in order to guarantee its descent. Moreover, we analyze penalization by perimeter as a regularization method, based on recent results on the convergence of Neumann problems and a generalization of Golab’s theorem. The behavior of the level set method and of the regularization procedure in presence of noise are tested in several numerical examples. It turns out that reconstructions of good quality can be obtained only for simple shapes or for unreasonably small noise levels. However, it seems reasonable that the quality of reconstructions improves by using more than a single boundary measurement, which is an interesting topic for future research.